Enhanced ROC Analysis

Usage

timeroc(
  data,
  elapsedtime,
  outcome,
  outcomeLevel,
  marker,
  timepoints = "12, 36, 60",
  method = "incident",
  bootstrapCI = FALSE,
  nboot = 100,
  plotROC = TRUE,
  plotAUC = TRUE,
  timetypeoutput = "months",
  showOptimalCutoff = TRUE,
  showMarkerStats = TRUE,
  compareBaseline = FALSE,
  smoothAUC = FALSE,
  analysisType = "timedep",
  compareROCs = FALSE,
  markers,
  rocComparison = "delong",
  youdenIndex = TRUE
)

Arguments

data: .
elapsedtime: .
outcome: .
outcomeLevel: .
marker: .
timepoints: .
method: .
bootstrapCI: .
nboot: .
plotROC: .
plotAUC: .
timetypeoutput: Time units for display in plots and results.
showOptimalCutoff: Calculate and display optimal cutoff points that maximize Youden index.
showMarkerStats: Display descriptive statistics for the marker variable.
compareBaseline: Compare marker performance to a baseline model (AUC = 0.5).
smoothAUC: Apply smoothing to the AUC over time plot for better visualization.
analysisType: Choose between time-dependent ROC analysis or general binary classification ROC.
compareROCs: Compare multiple ROC curves using statistical tests (DeLong test for binary ROC).
markers: Additional marker variables to compare against the primary marker.
rocComparison: Statistical method for comparing ROC curves (binary analysis only).
youdenIndex: Calculate Youden index (sensitivity + specificity - 1) for optimal threshold selection.

Value

A results object containing:

`results$text`					a html
`results$aucTable`					a table
`results$rocPlot`					an image
`results$aucPlot`					an image
`results$markerStats`					a table
`results$cutoffTable`					a table
`results$modelComparison`					a html
`results$clinicalInterpretation`					a html
`results$binaryROCTable`					a table
`results$rocComparison`					a table
`results$binaryROCPlot`					an image
`results$diagnosticPerformance`					a html

Tables can be converted to data frames with asDF or as.data.frame. For example:

results$aucTable$asDF

as.data.frame(results$aucTable)